Estimating snow water equivalent for a slightly tilted snow-covered prairie grass field by GPS interferometric reflectometry

Abstract

Snow water equivalent (SWE) measurements are necessary for the management of water supply and flood control systems in seasonal snow-covered regions. SWE measurements quantify the amount of water stored in snowpack; it can be estimated by the product of snow depth and density. In this paper, snow depth and density are estimated by a nonlinear least squares fitting algorithm. The inputs to this algorithm are global positioning system (GPS) signals and a simple GPS interferometric reflectometry model (GPS-IR) that incorporates a slightly tilted surface (GPS-IRT). The elevation angles of interest at the GPS receiving antenna are between 5° and 30°. A 1-day experiment with a snow-covered prairie grass field using GPS satellites PRN 15 and PRN 18 shows potential for inferring snow water equivalent using GPS-IRT. For this case study, the average inferred snow depth (12.4 cm) from the two satellite tracks underestimates the in situ measurements (17.6 cm ± 1.5 cm). However, the average inferred snow density (0.085 g∙cm-3) from the two satellite tracks is within the in situ measurement range (0.08 g∙cm-3 ± 0.02 g∙cm-3). Consequently, the average inferred SWE (1.05 g∙cm-2) from the two satellite tracks is within the in situ calculation range (1.40 g∙cm-2 ± 0.36 g∙cm-2). These results are also compared with the GPS-IR model.